Singapore's power grid operator handles hundreds of thousands of customer calls annually,with the majority related to power outages,billing inquiries,and service requests.Before automation,the operator faced significant challenges during monsoon seasons when call volumes spiked dramatically.Customers often waited 15 minutes or more to report an outage,and after-hours calls were frequently routed to voicemail,leaving residents frustrated and uninformed.This case study examines how the operator deployed Instadesk's 24/7 AI customer ChatBot to automate outage reporting,provide real-time restoration estimates,and proactively notify affected customers.The result was a 50% reduction in outage-related calls to human agents and a 70% faster response time for customers.
Customer Background and Pain Points
The Singapore-based operator serves 1.5M+residential and business users.Its call center only operated limited daytime hours,failing to cope with 5x call surges during monsoon seasons.Long waiting time and high call abandonment dragged down customer satisfaction for outage services.
Besides,the English-only IVR could not fit Singapore's multilingual demands covering Mandarin and Malay.The operator required a 24/7 tri-language solution to connect with the OMS system and deliver proactive service notifications.
The Solution:24/7 AI Customer Service Bot
After evaluating several vendors,the operator selected Instadesk's AI chatbot and voicebot platform.The solution was deployed in four weeks using Instadesk's pre-built utility templates.Key features implemented included:
•Multilingual support:The bot understands and responds in English,Mandarin,and Malay,automatically detecting the caller's language from their first sentence.
•Outage reporting automation:Customers can report outages via voice (phone call) or chat (website and mobile app).The bot collects the customer's address,a description of the issue,and any safety concerns (e.g.,sparking wires).It then creates a ticket directly in the OMS.
•Real-time restoration estimates:The bot queries the OMS for estimated repair times based on crew location and historical data.It provides these estimates to customers verbally or via chat.
Implementation and Results
The deployment was completed in four weeks.After six months of operation,the operator achieved the following results:
•Automation rate:60% of all outage-related calls were handled entirely by the AI bot without any human agent involvement.
•Average wait time:Dropped from 15 minutes during peak periods to under 3 minutes for calls that required agent escalation.
•Outage calls to human agents:Reduced by 50%,allowing agents to focus on complex issues and emergencies.
•Customer satisfaction:Increased from 68% to 86% for outage-related interactions.
The operator also reported significant cost savings.The bot handled an average of 8,000 calls per month that would have otherwise required agent time.At an estimated cost of $3 per agent call,the bot saved the operator approximately $24,000 per month,or $288,000 annually.The total investment in the bot was recouped within five months.
Key Lessons for Other Power Grid Operators
•Multilingual AI is essential for serving diverse populations.Training the bot on local dialects and common phrases improves accuracy and customer trust.
•Integration with OMS is critical for providing real-time restoration estimates.Without this,the bot can only give generic answers,which frustrates customers.
•Proactive notifications significantly reduce follow-up calls.Customers appreciate being updated without having to call again.
•Clear escalation paths for emergencies (e.g.,keywords like "fire" or "sparking wires") ensure that urgent issues receive immediate human attention.
Conclusion
Singapore's power grid operator proved that a 24/7 AI chatbot can dramatically improve outage handling,reduce wait times,and increase customer satisfaction.Instadesk's platform enabled rapid deployment,local language support,and seamless OMS integration.Other utilities facing similar challenges can achieve comparable results by following this case study’s approach.The operator is now expanding the bot to handle billing inquiries and service activation requests.
